Identifying application preemptive requests

ABSTRACT

A method for optimizing the number of pre-emptive service requests in an application based on identifying a plurality of pre-emptive execution eligible service requests. The method includes identifying one or more locations, associated with one or more service requests, respectively, in an application. Analyzing the one or more service requests based on the one or more locations. Determining if the one or more service requests are eligible for pre-emptive execution based on the analyzing, and responsive to determining the one or more service requests are eligible, outputting, by the one or more processors, one or more identities of the one or more service requests, respectively, for pre-emptive execution.

BACKGROUND OF THE INVENTION

The present invention relates generally to service requests inapplications and more specifically, to optimizing the number ofpre-emptive service requests in an application.

Distributed processing systems and applications typically require alevel of integration between applications. For instance, it is oftenrequired for an application to rely on a service provided by serviceprovider, wherein the service provider can be on-premise (e.g. providedlocally in a distributed processing environment, such as within a localarea network) or off-premise (e.g. provided remotely, such as via theInternet and/or within a cloud computing environment).

Response time is a key factor in application execution, wherein it iswidely recognized that a shorter response time is typically beneficial.The response time of an application can be adversely affected byservices which are called by the application. For example, anapplication can arrive at logic/instructions requiring theresults/output from a service and can then have to wait for theresult/output from the service to be provision, thus increasing theresponse time of the application.

In an attempt to address such an issue, a service can be called earlieron in the application logic flow (e.g. pre-emptively requested), sothat, by the point in the logic/instruction flow that the result/outputfrom the service is required, the result/output from the service isavailable (or a shorter wait for the result/output is required). Howeverlocating and/or identifying pre-emptive service requests can be verycumbersome.

SUMMARY

According to an embodiment of the present invention acomputer-implemented method for optimizing the number of pre-emptiveservice requests in an application based on identifying a plurality ofpre-emptive execution eligible service requests. The method includesidentifying, by one or more processors, one or more locations,associated with one or more service requests, respectively, in anapplication. Followed by analyzing, by the one or more processors, theone or more service requests based on the one or more locations.Subsequent to analyzing, determining, by the one or more processors, ifthe one or more service requests are eligible for pre-emptive executionbased on the analyzing, and responsive to determining the one or moreservice requests are eligible, outputting, by the one or moreprocessors, one or more identities of the one or more service requests,respectively, for pre-emptive execution.

According to an embodiment of the present invention, a computer programproduct for optimizing the number of pre-emptive service requests in anapplication based on identifying a plurality of pre-emptive executioneligible service requests. The computer program product includes one ormore computer readable storage devices and program instructions storedon the one or more computer readable storage devices. The stored programincluded program instructions to identify one or more locationsassociated with one or more service requests, respectively, in anapplication. Followed by program instructions to analyze the one or moreservice requests based on the one or more locations. Subsequent to theanalysis, program instructions to determine if the one or more servicerequests are eligible for pre-emptive execution based on the analyzing,and responsive to determining the one or more service requests areeligible, program instructions to output one or more identities of theone or more service requests, respectively, for pre-emptive execution.

According to an embodiment of the present invention, a computer systemcomprising: one or more computer processors; one or more computerreadable storage devices; program instructions stored on the one or morecomputer readable storage devices for execution by at least one of theone or more computer processors. The stored program instructions includeprogram instructions to identify one or more locations associated withone or more service requests, respectively, in an application. Followedby program instructions to analyze the one or more service requestsbased on the one or more locations. Subsequent to the analysis, programinstructions to determine if the one or more service requests areeligible for pre-emptive execution based on the analyzing; andresponsive to determining the one or more service requests are eligible,program instructions to output one or more identities of the one or moreservice requests, respectively, for pre-emptive execution.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention will now be described, byway of example only, with reference to the following drawings, in which:

FIG. 1 depicts a cloud computing environment according to an embodimentof the present invention;

FIG. 2 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 3 is a functional block diagram illustrating a distributed dataprocessing environment, in accordance with an embodiment of the presentinvention;

FIG. 4 is a flowchart depicting a method for optimizing the number ofpre-emptive service requests in an application based on identifying aplurality of pre-emptive execution eligible service requests accordingto an embodiment; and

FIG. 5 depicts a block diagram of components of the server computerexecuting the calibration component within the distributed dataprocessing environment of FIG. 1, in accordance with an embodiment ofthe present invention.

DETAILED DESCRIPTION

It should be understood that the Figures are merely schematic and arenot drawn to scale. It should also be understood that the same referencenumerals are used throughout the Figures to indicate the same or similarparts.

In the context of the present application, where embodiments of thepresent invention constitute a method, it should be understood that sucha method is a process for execution by a computer, i.e. is acomputer-implementable method. The various steps of the method thereforereflect various parts of a computer program, e.g. various parts of oneor more algorithms.

Also, in the context of the present application, a (applicationprocessing) system can be a single device or a collection of distributeddevices that are adapted to execute one or more embodiments of themethods of the present invention. For instance, a system can be apersonal computer (PC), a server or a collection of PCs and/or serversconnected via a network such as a local area network, the Internet andso on to cooperatively execute at least one embodiment of the methods ofthe present invention.

The present invention seeks to provide a method for identifyingpre-emptive service requests that can provide support for integratingapplications or services in scalable service architectures (e.g. a cloudcomputing environment). The present invention further seeks to provide acomputer program product including computer program code forimplementing the method when executed on a processor of a processingsystem. The present invention yet further seeks to provide a processingsystem adapted to execute this computer program code.

Proposed are concepts for analyzing an application that can comprise alarge or very large number (e.g. 10,000+) of separate programs (such asan application in a CICS installation). The analysis can identify and/orassist an application owner to identify services and/or servicerequests/calls where issuing a pre-emptive request/call can help toreduce response times. Thus, embodiments can be particularly for use inconjunction with a run-time environment that is capable of callingservices pre-emptively. However, it is also envisaged that embodimentscan be used in a ‘stand-alone’ manner. For example, embodiment can beused in a tool that identifies cases where an existing application couldbe enhanced by modifying it to call certain services pre-emptively.

Embodiment of the present invention can identify a pre-emptive servicerequest for an application by analyzing the application to identify aservice request of the application. By referring to indicators ofsuitability for pre-emptive execution, it can be determined whether ornot the service request can be executed pre-emptively (e.g. at anearlier point in the application logic of the application). Suchembodiments of the present invention can be implemented as a softwaretool, thus facilitating the identification of services that can berequested earlier in application logic and when such a service can beable to be called.

By interrogating application execution using software tooling focused onexecution trace, monitoring information, and/or application source code,embodiments of the present invention can identify one or more servicerequests that can be invoked at an earlier point in the applicationlogic; therefore, improving the art by optimizing the identification ofeligible pre-emptive service requests in an application. Embodiments cantherefore enable a search for pre-emptive services within applicationcode to be conducted programmatically (e.g. via tooling) where a largenumber of applications exist. By invoking these service requests earlierthan would otherwise be done in the normal execution of the application,overall application response time can be reduced (e.g. because thewaiting time for the service request can be reduced or even eliminated).

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations can be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The terminology used herein was chosen to best explain the principles ofthe embodiment, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

Illustrative embodiments can be utilized in many different types ofapplication processing environments. Illustrative embodiments can, forexample, be employed in relation to stateless and scalable cloud-basedapplications for data and/or event processing.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model can includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but can be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It can be managed by the organization or a third party andcan exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It can be managed by the organizations or a third partyand can exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 1, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N can communicate. Nodes 10 cancommunicate with one another. They can be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities can be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 can provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources can include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Application processing 85 providesapplication processing according to proposed embodiments.

Workloads layer 90 provides examples of functionality for which thecloud computing environment can be utilized. Examples of workloads andfunctions which can be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and pre-empting service component 122.

A proposed concept can enhance an event processing system by reducingcosts per user while maximizing quality of service. Embodiments can alsoenable flexibility to provide higher qualities of service for particularusers (e.g. user paying an additional fee). Such proposals can extend orimprove the processing capabilities or efficiency of an IntegrationSoftware as a Service (iSaaS) system or component.

FIG. 3 is a functional block diagram illustrating a distributed dataprocessing environment, generally designated 300, in accordance with oneembodiment of the present invention. The term “distributed” as used inthis specification describes a computer system that includes multiple,physically distinct devices that operate together as a single computersystem. FIG. 3 provides only an illustration of one implementation anddoes not imply any limitations with regard to the environments in whichdifferent embodiments can be implemented. Many modifications to thedepicted environment can be made by those skilled in the art withoutdeparting from the scope of the invention as recited by the claims.

Distributed data processing environment 100 includes computing device110 and server computer 120, interconnected over network 130. Network130 can be, for example, a telecommunications network, a local areanetwork (LAN), a wide area network (WAN), such as the Internet, or acombination of the three, and can include wired, wireless, or fiberoptic connections. Network 130 can include one or more wired and/orwireless networks that are capable of receiving and transmitting data,voice, and/or video signals, including multimedia signals that includevoice, data, and video information. In general, network 130 can be anycombination of connections and protocols that will supportcommunications between computing device 110 and server computer 120, andother computing devices (not shown in FIG. 1) within distributed dataprocessing environment 100.

In various embodiments, computing device 110 can be, but is not limitedto, a standalone device, a server, a laptop computer, a tablet computer,a netbook computer, a personal computer (PC), a smart phone, a desktopcomputer, a smart television, a smart watch, any programmable electroniccomputing device capable of communicating with various components anddevices within distributed data processing environment 100, via network120 or any combination therein. In general, computing device 110 isrepresentative of any programmable mobile device or a combination ofprogrammable mobile devices capable of executing machine-readableprogram instructions and communicating with users of other mobiledevices via network 130 and/or capable of executing machine-readableprogram instructions and communicating with server computer 120. Inother embodiments, computing device 110 can represent any programmableelectronic computing device or combination of programmable electroniccomputing devices capable of executing machine readable programinstructions, manipulating executable machine readable instructions, andcommunicating with server computer 120 and other computing devices (notshown) within distributed data processing environment 100 via a network,such as network 130. Computing device 110 includes an instance of userinterface 106. Computing device 110 and user interface 106 allow a userto interact with pre-empting service component 122 in various ways, suchas sending program instructions, receiving messages, sending data,inputting data, editing data, correcting data and/or receiving data.

User interface 106 provides an interface to pre-empting servicecomponent 122 on server computer 120 for a user of computing device 110.In one embodiment, user interface 106 can be a graphical user interface(GUI) or a web user interface (WUI) and can display text, documents, webbrowser windows, user options, application interfaces, and instructionsfor operation, and include the information (such as graphic, text, andsound) that a program presents to a user and the control sequences theuser employs to control the program. In another embodiment, userinterface 106 can also be mobile application software that provides aninterface between a user of computing device 110 and server computer120. Mobile application software, or an “app,” is a computer programdesigned to run on smart phones, tablet computers and other mobiledevices. In an embodiment, user interface 106 enables the user ofcomputing device 110 to send data, input data, edit data, correct dataand/or receive data.

Server computer 120 can be a standalone computing device, a managementserver, a web server, a mobile computing device, or any other electronicdevice or computing system capable of receiving, sending, and processingdata. In other embodiments, server computer 120 can represent a servercomputing system utilizing multiple computers as a server system, suchas in a cloud computing environment. In another embodiment, servercomputer 120 can be a laptop computer, a tablet computer, a netbookcomputer, a personal computer (PC), a desktop computer, a personaldigital assistant (PDA), a smart phone, or any other programmableelectronic device capable of communicating with computing device 110 andother computing devices (not shown) within distributed data processingenvironment 100 via network 130. In another embodiment, server computer120 represents a computing system utilizing clustered computers andcomponents (e.g., database server computers, application servercomputers, etc.) that act as a single pool of seamless resources whenaccessed within distributed data processing environment 100. Servercomputer 120 includes pre-empting service component 122 and database124. Server computer 120 can include internal and external hardwarecomponents, as depicted and described in further detail with respect toFIG. 3.

Database 124 and/or local storage 108 can be a data repository and/or adatabase that can be written to and read by one or a combination ofdisease progression component 110, server computer 120 and/or computingdevice 110. In the depicted embodiment, database 124 resides on servercomputer 120 and local storage 108 is housed on computing device 110.However, in another embodiment, database 124 and/or local storage 108can reside elsewhere within distributed data processing environment 100provided coverage assessment program 110 has access to database 124. Adatabase is an organized collection of data. Database 124 and/or localstorage 108 can be implemented with any type of storage device capableof storing data and configuration files that can be accessed andutilized by server computer 120 and/or computing device 110, such as adatabase server, a hard disk drive, or a flash memory. In otherembodiments, database 124 and/or local storage 108 can be hard drives,memory cards, computer output to laser disc (cold storage), and/or anyform of data storage known in the art. In various embodiments can storedata and/or discovered shortcuts to database 124 and/or local storage108. In various embodiments, pre-empting service component 122 canretrieve, access, and/or use previously stored data from database 124and/or local storage 108.

In an exemplary embodiment, pre-empting service component 122 is housedon server computer 120. In some embodiments, pre-empting servicecomponent 122 can be housed on computing device 110. In otherembodiments, pre-empting service component 122 can be a standalonedevice and/or housed on a separate component (computing device and/orserver computer) not depicted in FIG. 3. In various embodiments,pre-empting service component 122 can identify service requests that canbe invoked at an earlier point in the application logic. It should benoted that the service request can include a path and/or route forpre-emptive execution, as it is understood in the art.

For example, if a user assumes an application which at some point in itsprocessing is required to get a customer's address in view of a givenhouse number and/or postcode, it is typical that the application willhave done some sort of processing before it gets to the stage ofrequiring the address. The application will then request the addressfrom the external service and wait for the response. Once the addressreply is obtained, the application can continue. In this particularexample, pre-empting service component 122 can identify that the servicerequest can safely be made (e.g. communicated or executed) at an earlierpoint in the application logic. Based on this identification, the sourcecode can be modified so that, when run, the service request for theaddress can be made as soon as the transaction is started (or at leastwhen a required input for the service request is available).

In various embodiments, pre-empting service component 122 can providefor a decrease in an overall application response time, and this can beprovided with a decreased risk associated with a change and/or a reducedinitial understanding of the application. In various embodiments,pre-empting service component 122 can also address the issue that, whenpresented with all of an organization's application logic, it ispractically impossible for a human to articulate the best services to bemade pre-emptively (because it can require a deep understand of everyapplication). In various embodiments, pre-empting service component 122can identify services that can be pre-emptively called (e.g. executedearly and/or in advance of the point at which they would normally beaccording to the conventional application logic).

In one embodiment, a pre-empting service component 122 can determine ifthe service request can be executed at an earlier point in theapplication logic of an application, and can determine the servicerequest is based on trace information obtained from an execution of theapplication. For example, the application can comprise a trace elementthat generates a trace event during execution of the application, andthe trace information can then comprise information relating to thetrace event. Examples of trace information can include, but are notlimited to: time of the event; data associated with the event; eventtype; I/O data; response codes; etc. In this way, embodiments canimplement trace analysis concepts.

By way of another example, a step of determining if the service requestcan be executed at an earlier point in the application logic of theapplication can be based on monitoring information obtained frommonitoring an execution of the application. Examples of monitoringinformation can include: time of events; external/internal calls;resource usage; I/O data; status; usage counts; execution time; etc.

In another example, analyzing the application can involve analyzing atleast one of: source code of the application: application logic of theapplication; a component or resource of the application; status changesof the application; and input/output data flows of the application.

In determining whether an identified service request is suitable forpre-emptive execution, a property or characteristic of the identifiedservice request can be considered against one or more indicators ofsuitability for pre-emptive execution. Such indicators can, for example,include predetermined types or value of: input data; output data;service request timing; execution context (e.g. service executioncontext within the application); service request type; service requestoriginator; and a service request identifier. For instance, theidentified service can be checked against a list or services that aresuitable for pre-emptive execution (either because they are called in atransaction or because they are read-only for example).

Illustrative embodiments can therefore provide a tool that helpsidentify service requests for pre-emptive calling. It can do this byanalyzing the processing performance performed by a system in responseto specific requests. Proposed concepts can thus provide informationthat can be used to decide which cases merit further investigation. Suchinvestigation can then result in outputting identities of servicerequests for pre-emptive execution, which can lead to optimizing theidentification of eligible pre-emptive service requests in anapplication.

Rather than analyzing input data at the time the data is entered,proposed embodiments can analyze the process of processing input data,for example by analyzing program code or traces of program execution.Further, embodiments can avoid using categorization to establishpotential relevance/utility of pre-emptive calls. Instead, proposedembodiments can observe actually service requests/calls used in existingprocessing and then identify those that can benefit from pre-emptiveprocessing/execution.

Many different ways to identify pre-emptive service requests can beemployed by embodiments, and these can be implemented in isolation or incombination. Modifications and additional steps to a traditional(application) processing systems can also be proposed which can enhancethe value and utility of the proposed concepts.

An example according to the above method depicted in Diagram 1 can beimplemented in a Customer Information Control System (CICS®) executionenvironment and workstation tooling environment. However, it will beappreciated that there are other environments and platforms to whichembodiment can be appropriate. Also, although embodiments of pre-emptingservice component 122 have been described as providing and/orimplementing tools for interrogating application execution traces, inother embodiments pre-empting service component 122 can provide and/orimplement tools for interrogating collected monitoring informationand/or original source code.

A CICS® provides an environment in which applications are run. The CICSprogramming interface provides clearly identifiable points ofapplication logic where user data is updated (such as GET/PUTcontainers) as well as the input and time of service invocations (suchas PROGRAM LINK, INVOKE SERVICE, START etc).

In various embodiments, pre-empting service component 122 can identifyopportunities where service requests can be initiated earlier (e.g.pre-emptively invoked) to reduce a response time attributed to waitingfor one or more responses. In various embodiments, service requestscould be inferred by pre-empting service component 122, for example,when execution control is passed outside of this program. However, insome embodiments, a user create/generate a list of services that aresuitable for the pre-emptive calling (either because they are called intransaction or because they are read-only for example), via UI 106. Someembodiments can then assess and/or prioritize identified events based onthe user generated list of services to determine which service and/oridentified event(s) benefit from being called earlier (e.g.pre-emptively called).

Furthermore, in one example, application (ProgA) executes and eventuallyrequests the canonical address of the user based upon the house numberand postcode provided to the application. An exemplary process flow ofthis first example is illustrated in Diagram 1, wherein the serviceprovider of the AddressService takes a few seconds to respond.

However, in various embodiments, pre-empting service component 122 canidentify that the input to the service originates from a named inputcontainer. Additionally, in various embodiments, pre-empting servicecomponent 122 can identify that the container is never updated beforethe service request is made. Therefore, in various embodiments,pre-empting service component 122 can suggest that the service call canbe initiated immediately upon application initiation, thus resulting ina process flow as illustrated in Diagram 2.

Therefore, in this particular example, pre-empting service component 122provides information that the “GetAddress” service for “AddressService”is a good for calling pre-emptively as soon as PROGA is initiated.

In another example, there is a subroutine within the application (ProgA)that updates the input container to replace the address from aresidential to business address. In this particular example, after thesubroutine performs the container is not updated again before theservice request is made. An exemplary process flow of this firstscenario is illustrated in Diagram 3, wherein the relative timing of thecontainer being updated is depicted by an arrow labelled “AddressContainer Updated”.

In this particular example, pre-empting service component 122 cantherefore provide information that the “GetAddress” service for“AddressService” is a good for calling pre-emptively as soon as theADDRESS container is updated (as depicted in Diagram 3).

It will thus be appreciated that optimizing the identification ofeligible pre-emptive service requests in an application improvesefficiency. Therefore, it is critical to locate and identify pre-emptiveservice requests. Additionally, there can be a reduced risk associatedwith arranging such pre-emptive requests by not requiring the user tounderstand all code paths of the application logic.

Furthermore, in an embodiment, pre-empting service component 122 canobtain an understanding of the actual response time of theAddressService (by using monitoring information for example). In thisparticular embodiment, pre-empting service component 122 can suggest arange of the source code in which the service request can be made inorder for the response to be available in time. For example, if theAddressService takes one (“1”) second to respond and the result isrequired five (“5”) seconds into the execution of the application,pre-empting service component 122 can determine that the service doesnot need to be initiated immediately (but can instead be initiated anytime in the first four (“4”) seconds), for the result to be availablewhen required. Such a proposed approach can offer a method for orderingand giving priorities for situations where more than one service isidentified as being able to be pre-emptively invoked.

In another example, pre-empting service component 122 can also beadapted to cater for another scenario wherein an organization has manyapplications, which make thousands of external service requests. Anapproach which provides a high number (e.g. around 1000 or more)possible service requests that could potentially be made pre-emptivelywill not be considered useful. In this particular example, to addressthis, pre-empting service component 122 can prioritize the large numberof identified service requests that could potentially be madepre-emptively. In this particular example, pre-empting service component122 can do this in a number of ways, such as: by prioritizing servicecalls by frequency of use; and/or by ordering/arranging the suggestionlist by how early the preemptive calls can be made (e.g. if the servicecan be invoked a single instruction ahead of where it currently is, itcan be would be a low priority, whereas a service call that can beinitiated at program startup can be a high priority).

In various embodiments, pre-empting service component 122 can enhance anevent processing system by reducing costs per user while maximizingquality of service. In various embodiments, pre-empting servicecomponent 122 can also enable flexibility to provide higher qualities ofservice for particular users (e.g. user paying an additional fee). Inthese embodiments, pre-empting service component 122 can extend orimprove the processing capabilities or efficiency of a iSaaS system orcomponent.

FIG. 4 is a flowchart depicting a method for outputting pre-emptiveservice request s, on server computer 120 within distributed dataprocessing environment 300 of FIG. 3, in accordance with an embodimentof the present invention. It should be appreciated that FIG. 4 providesonly an illustration of one implementation and does not imply anylimitations with regard to the environments in which differentembodiments can be implemented. Many modifications to the depictedenvironment can be made. In an embodiment, and an exemplary context forthe method, the processing system is adapted to implement services in acloud environment, and more particularly the processing system isadapted to implement a part of a micro-service-oriented architecture(mirco-service). Accordingly, a service request of the application maycomprise a request for a micro-service. Generally, a micro-service is amethod of developing software applications as a suite of independentlydeployable, small, modular services in which each service runs a uniqueprocess and communicates through a well-defined, lightweight mechanismto serve a goal.

In step 410, pre-empting service component 122 identifies a servicerequest of the application. In various embodiments, pre-empting servicecomponent 122 can identify where the service request of the applicationtakes place, i.e., the location of the service request in theapplication and/or the logic path(s) to the service request. Forexample, an application which at some point in its processing isrequired to retrieve the customers address given the house number andpostcode. In this example, it is typical that the application will havedone some sort of processing before it gets to the stage of requiringthe address. It will then request the address from the external serviceand wait for the response, which constitutes a service request. In thisexample, once the address reply is obtained, the application cancontinue. It should be noted that the use of location refers to thelocation of the service request in the application and/or the logicpath(s) to the service request.

In step 415, pre-empting service component 122 analyzes the identifiedservice request. In various embodiments, pre-empting service component122 can analyze one or more identified service request of anapplication. In various embodiments, analyzing the one or more servicerequests can comprise analyzing source code of the application,application logic of the application, a component or resource of theapplication, status changes of the application, and/or input/output dataflows of the application.

In step 420, pre-empting service component 122 determines if the servicerequest is suitable/eligible for pre-emptive execution. In variousembodiments, pre-empting service component 122 can determine if one ormore service requests can be executed at an earlier point in theapplication logic of the application based on one or more indicators ofsuitability for pre-emptive execution. Such indicators of suitabilityfor pre-emptive execution can be but are not limited to: input data;output data; service request timing; service request type; servicerequest originator; and a service request identifier. For example, theidentified service request can be checked against one or more indicatorsof suitability by matching characteristics and/or properties of theservice request and/or the service against the indicators.

In another embodiment, pre-empting service component 122 can determineif one or more service request can be executed at an earlier point inthe application logic of the application based on trace informationobtained from an execution of the application. For example, theapplication can comprise a trace element that generates a trace eventduring execution of the application, and the trace information can thencomprise information relating to the trace event. Such trace informationcan be analyzed to determine if the service request can be executed atan earlier point in the application logic of the application. In adifferent embodiment, pre-empting service component 122 can determine ifthe service request can be executed at an earlier point in theapplication logic of the application based on monitoring informationobtained from monitoring an execution of the application.

In various embodiments, if pre-empting service component 122 determinesthat the service request can be executed at an earlier point in theapplication logic of the application (yes, step) the method proceeds tostep 430. However, in various embodiments, if pre-empting servicecomponent 122 determines that the service request cannot be executed atan earlier point in the application logic of the application (No, step),pre-empting service component 122 can return to step 410 to identifyanother service request. In another embodiment, not depicted in FIG. 4,if pre-empting service component 122 determines that the service requestcannot be executed at an earlier point in the application logic of theapplication (No, step), method can end.

In step 425, pre-empting service component 122 outputs an identity of aservice request for pre-emptive execution. In various embodiments,pre-empting service component 122 can output one or more pre-emptiveservice requests based on the one or more suitable/eligible servicerequests. For example, such identification of an outputted pre-emptiveservice request can be implemented by way of a flag or status indicator,such as a simple ‘on/off’ indicator or a more scalar indicator like a‘score’, ‘probability’ or ‘ stability value’ (which can allow identifiedservice requests to be ordered later). In various embodiments, themethod can then return to step 415 to repeat the process of identifyinganother service request (if appropriate). In various embodiments,responsive to determining the one or more service requests are eligible,pre-empting service component 122 can output one or more identities ofthe one or more service requests, respectively, for pre-emptiveexecution. An Identity can be, but is not limited to, a pointerlocation, one or more line numbers in a source code, module name, amemory address location, a function name, an indicator, and/or any otherforms of identifying and/or labeling service requests and/or source codeknown in the art.

FIG. 5 depicts computer system 500, where server computer 120 representsan example of computer system 500 that includes disease progressioncomponent 122. The computer system includes processors 501, cache 503,memory 502, persistent storage 505, communications unit 507,input/output (I/O) interface(s) 506 and communications fabric 504.Communications fabric 504 provides communications between cache 503,memory 502, persistent storage 505, communications unit 507, andinput/output (I/O) interface(s) 506. Communications fabric 504 can beimplemented with any architecture designed for passing data and/orcontrol information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system. For example,communications fabric 504 can be implemented with one or more buses or acrossbar switch.

Memory 502 and persistent storage 505 are computer readable storagemedia. In this embodiment, memory 502 includes random access memory(RAM). In general, memory 502 can include any suitable volatile ornon-volatile computer readable storage media. Cache 503 is a fast memorythat enhances the performance of processors 501 by holding recentlyaccessed data, and data near recently accessed data, from memory 502.

Program instructions and data used to practice embodiments of thepresent invention may be stored in persistent storage 505 and in memory502 for execution by one or more of the respective processors 501 viacache 503. In an embodiment, persistent storage 505 includes a magnetichard disk drive. Alternatively, or in addition to a magnetic hard diskdrive, persistent storage 505 can include a solid state hard drive, asemiconductor storage device, read-only memory (ROM), erasableprogrammable read-only memory (EPROM), flash memory, or any othercomputer readable storage media that is capable of storing programinstructions or digital information.

The media used by persistent storage 505 may also be removable. Forexample, a removable hard drive may be used for persistent storage 505.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage505.

Communications unit 507, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 507 includes one or more network interface cards.Communications unit 507 may provide communications through the use ofeither or both physical and wireless communications links. Programinstructions and data used to practice embodiments of the presentinvention may be downloaded to persistent storage 505 throughcommunications unit 507.

I/O interface(s) 506 enables for input and output of data with otherdevices that may be connected to each computer system. For example, I/Ointerface 506 may provide a connection to external devices 508 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 508 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention can be stored on such portablecomputer readable storage media and can be loaded onto persistentstorage 505 via I/O interface(s) 506. I/O interface(s) 506 also connectto display 509.

Display 509 provides a mechanism to display data to a user and may be,for example, a computer monitor.

1. A method for optimizing the number of pre-emptive service requests inan application based on identifying a plurality of pre-emptive executioneligible service requests, the method comprising: identifying, by one ormore processors, one or more locations, associated with one or moreservice requests, respectively, in an application; analyzing, by the oneor more processors, the one or more service requests based on the one ormore locations; determining, by the one or more processors, if the oneor more service requests are eligible for pre-emptive execution based onthe analyzing; and responsive to determining the one or more servicerequests are eligible, outputting, by the one or more processors, one ormore identities of the one or more service requests, respectively, forpre-emptive execution.
 2. The method of claim 1, wherein determiningfurther comprises monitoring execution of the application based on atleast one of time of events, external calls, internal calls, resourceusage, I/O data, status, usage counts or execution time.
 3. The methodof claim 1, wherein determining service request eligibility is based ontrace information obtained from an execution of the application.
 4. Themethod of claim 3, wherein the determining service request eligibilitycomprises a trace element that generates a trace event during executionof the application, and wherein the trace information comprisesinformation relating to the trace event.
 5. The method of claim 1,wherein analyzing further comprises at least one of: interpreting sourcecode of the application, logic flow of the application, a component ofthe application, a resource of the application, external calls of theapplication, internal calls of the application, timing of applicationevents, status changes of the application, input data flows of theapplication, or output data flows of the application.
 6. The method ofclaim 1, wherein the one or more indicators of suitability forpre-emptive execution comprise at least one of: input data, output data,service request timing, service request type, execution context, servicerequest originator, or a service request identifier.
 7. The method ofclaim 1, wherein the service request comprises a request for amicro-service.
 8. A computer program product for optimizing the numberof pre-emptive service requests in an application based on identifying aplurality of pre-emptive execution eligible service requests, thecomputer program product comprising: one or more computer readablestorage devices and program instructions stored on the one or morecomputer readable storage devices, the stored program instructionscomprising: program instructions to identify one or more locationsassociated with one or more service requests, respectively, in anapplication; program instructions to analyze the one or more servicerequests based on the one or more locations; program instructions todetermine if the one or more service requests are eligible forpre-emptive execution based on the analyzing; and responsive todetermining the one or more service requests are eligible, programinstructions to output one or more identities of the one or more servicerequests, respectively, for pre-emptive execution.
 9. The computerprogram product of claim 8, wherein determining further comprisesmonitoring execution of the application based on at least one of time ofevents, external calls, internal calls, resource usage, I/O data,status, usage counts or execution time.
 10. The computer program productof claim 8, wherein determining service request eligibility is based ontrace information obtained from an execution of the application.
 11. Thecomputer program product of claim 10, wherein the determining servicerequest eligibility comprises a trace element that generates a traceevent during execution of the application, and wherein the traceinformation comprises information relating to the trace event.
 12. Thecomputer program product of claim 8, wherein analyzing further comprisesat least one of: interpreting source code of the application, logic flowof the application, a component of the application, a resource of theapplication, external calls of the application, internal calls of theapplication, timing of application events, status changes of theapplication, input data flows of the application, or output data flowsof the application.
 13. The computer program product of claim 8, whereinthe one or more indicators of suitability for pre-emptive executioncomprise at least one of: input data, output data, service requesttiming, service request type, execution context, service requestoriginator, or a service request identifier.
 14. The computer programproduct of claim 8, wherein the service request comprises a request fora micro-service.
 15. A computer system comprising: one or more computerprocessors; one or more computer readable storage devices; programinstructions stored on the one or more computer readable storage devicesfor execution by at least one of the one or more computer processors,the stored program instructions comprising: program instructions toidentify one or more locations associated with one or more servicerequests, respectively in an application; program instructions toanalyze the one or more service requests based on the one or morelocations; program instructions to determine if the one or more servicerequests are eligible for pre-emptive execution based on the analyzing;and responsive to determining if the one or more service requests areeligible, program instructions to output one or more identities of theone or more service requests, respectively, for pre-emptive execution.16. The computer system of claim 15, wherein determining furthercomprises monitoring execution of the application based on at least oneof time of events, external calls, internal calls, resource usage, I/Odata, status, usage counts or execution time.
 17. The computer system ofclaim 15, wherein determining service request eligibility is based ontrace information obtained from an execution of the application.
 18. Thecomputer system of claim 17, wherein the determining service requesteligibility comprises a trace element that generates a trace eventduring execution of the application, and wherein the trace informationcomprises information relating to the trace event.
 19. The computersystem of claim 15, wherein analyzing further comprises at least one of:interpreting source code of the application, logic flow of theapplication, a component of the application, a resource of theapplication, external calls of the application, internal calls of theapplication, timing of application events, status changes of theapplication, input data flows of the application, or output data flowsof the application.
 20. The computer system of claim 15, wherein the oneor more indicators of suitability for pre-emptive execution comprise atleast one of: input data, output data, service request timing, servicerequest type, execution context, service request originator, or aservice request identifier.